Article ID Journal Published Year Pages File Type
10403602 IFAC Proceedings Volumes 2005 6 Pages PDF
Abstract
In this paper a nonlinear system identification methodology based on a polynomial NARMAX model representation is considered. Algorithms for structure selection and parameter estimation are presented and evaluated. The goal of the procedure is to provide a nonlinear model characterized by a low complexity and that can be efficiently used in industrial applications. The methodology is illustrated by means of an automotive case study namely a variable geometry turbocharged diesel engine. The nonlinear model representing the relation between the variable geometry turbine command and the intake manifold air pressure is identified from data and validated.
Related Topics
Physical Sciences and Engineering Engineering Computational Mechanics
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